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The purpose of the paper is to predict the residual life of liquid-storage tank to ensure safety and long-term service life of the structure.

The paper carried out the stress analysis of the wall plate and bottom plate of the liquid-storage tank, and the influence of circumferential stress on the tank is considered. On the other hand, considering the influence of the tank wall surface on the tank life, based on the Paris law, the surface processing coefficient and surface roughness coefficient are introduced to improve the Paris law.

The effectiveness of the improved model is verified by comparing with theoretical and experimental data, which provide a new method for the prediction of the remaining service life of the tank. Combined with the fatigue crack data in the test report and the calculated circumferential stress, the residual life of the storage tank is predicted.

The improved model provides a new method for the prediction of the remaining service life of the tank.

The purpose of this paper is to explore the potential of enriching the library subject headings with folksonomy for enhancing the visibility and usability of the library subject headings.

The WorldCat-million data set and SocialBM0311 are preprocessing and over 210,000 library catalog records and 124,482 non-repeating tags were adopted to construct the matrix to observe the semantic relation between library subject headings and folksonomy. The proposed system is compared with the state-of-the-art methods and the parameters are fixed to obtain effective performance.

The results demonstrate that by integrating different semantic relations from library subject headings and folksonomy, the system’s performance can be improved compared to the benchmark methods. The evaluation results also show that the folksonomy can enrich library subject headings through the semantic relationship.

The proposed method simultaneous weighted matrix factorization can integrate the semantic relation from the library subject headings and folksonomy into one semantic space. The observation of the semantic relation between library subject headings and social tags from folksonomy can help enriching the library subject headings and improving the visibility of the library subject headings.

The online users’ characteristic information can provide decision support for policy-designing and construction of public strategies. Hence, this paper aims to conduct online public opinion mining on the recovery policy stimulating the economies stroked by COVID-19 epidemic. Also, sentimental analysis is performed to uncover the posters’ emotion towards the target policy.

This paper adopts bidirectional encoder representations from transformers (BERT) as classifier in classification tasks, including misinformation detection, subject analysis and sentimental analysis. Meanwhile, latent Dirichlet allocation method and sentiment formulations are implemented in topic modelling and sentiment analysis.

The experimental results indicate that public opinion is mainly non-negative to the target policy. The positive emotions mainly focus on the benefits that the recovery policy might bring to stimulate economy. On the other hand, some negative opinions concerned about the shortcomings and inconvenience of the target policy.

The authors figured out the key factors focused by the public opinion on the target recovery policy. Also, the authors indicated pros and cons of the recovery policy by analysing the emotion and the corresponding topics of the public opinion on social media. The findings of the paper can be generalized in other countries theoretically to help them design recovery policy against COVID-19.

People often need to make intertemporal choices in their daily life, such as savings and spending, but their decisions are not always entirely rational. The purpose of this paper is to study the effect of hunger on intertemporal choices and the moderating effect of sensitivity to reward.

Two studies verified these two hypotheses. The first study confirmed the existence of the main effect by manipulating food aroma. In the second study, by manipulating hunger with images, the authors increased external validity of the study and confirmed the regulation of the sensitivity of rewards.

The authors found that hungry people prefer to reap the benefits as early as possible in an intertemporal choice; this effect is significant only for those people who are sensitive to reward.

The research contributes to understand more about which factors will influence Chinese residents’ decisions on savings and spending. It also has practical implication for government policy, for example, proposing new ideas for reducing household savings rate and stimulating consumption.

The results confirmed that hunger significantly affects consumers’ intertemporal choices, which broadened the scope of researches on the factors that influence intertemporal choice, and advanced the study on the influence of individual’s physiological state on intertemporal choices. This study filled the gaps in previous researches, and opened up new research ideas for interdisciplinary study.

The construction industry accounts for a large proportion of the economy of developing countries, but the connotation and influencing factors of high-quality development (HQD) are still unclear. This study aims to gain a more comprehensive insight into the current development status of the regional construction industry under China's HQD orientation and the obstructive factors affecting its development and to provide informative suggestions for its HQD prospects.

In this study, the construction industry of 16 cities in the Chengdu-Chongqing economic circle (CCEC), a new region in southwest China, was used as the research object to collect data from the 2006–2019 yearbooks, construct an evaluation index system for HQD of the construction industry, derive the development level of the construction industry using the entropy value method and spatial autocorrelation method and then apply the barrier Diagnostic model was used to compare and analyze the impact level of each index.

In terms of the time dimension, the development of the construction industry in CCEC is characterized by “high in the twin core and low in the surrounding area”, with unbalanced and insufficient development; in terms of spatial correlation, some factors have positive aggregation in spatial distribution, but the peripheral linkage decreases; through barrier analysis, the impact of different barrier factors is different.

This paper will help governments and enterprises in developing countries to make urban planning and management policies to fundamentally improve the development of the construction industry in underdeveloped regions.

The aim of this article is to present a PIN (pedestrian inertial navigation) solution that incorporates altitude error correction, which eliminates the altitude error accurately without using external sensors. The main problem of PIN is the accumulation of positioning errors due to the drift caused by the noise in the sensors. Experiment results show that the altitude errors are significant when navigating in multilayer buildings, which always lead to localization to incorrect floors.

The PIN proposed is implemented over an inertial navigation systems (INS) framework and a foot-mounted IMU. The altitude error correction idea is identifying the most probable floor of each horizontal walking motion. To recognize gait types, the walking motion is described with angular rate measured by IMU, and the dynamic time warping algorithm is used to cope with the different dimension samples due to the randomness of walking motion. After gait recognition, the altitude estimated with INS of each horizontal walking is checked for association with one of the existing in a database.

Experiment results show that high accuracy altitude is achieved with altitude errors below 5 centimeters for upstairs and downstairs routes in a five floors building.

The main limitations of the study is the assumption that accuracy floor altitude information is available.

Our PIN system eliminates altitude errors accurately and intelligently, which benefits from the new idea of combination of gait recognition and map-matching. In addition, only one IMU is used which is different from other approach that use external sensors.

Based on the perspectives of social capital, image motivation and motivation affordances, this paper explores the direct and moderation effects of different kinds of motivations (i.e. relationship-based motivation, community-based motivation and individual-based motivation) on users' continuous knowledge contributions in social question and answer (Q&A) communities.

The authors collect the panel data of 10,193 users from a popular social Q&A community in China. Then, a negative binomial regression model is adopted to analyze the collected data.

The paper demonstrates that social learning, peer recognition and knowledge seeking positively affect users' continuous contribution behaviors. However, the results also show that social exposure has the opposite effect. In addition, self-presentation is found to moderate the influence of social factors on users' continuous use behaviors, while the moderation effect of motivation affordances has no significance.

First, this study develops a comprehensive motivation framework that helps gain deeper insights into the underlying mechanism of knowledge contribution in social Q&A communities. Second, this study conducts panel data analysis to capture the impacts of motivations over time, rather than intentions at a fixed time point. Third, the findings can help operators of social Q&A communities to optimize community norms and incentive mechanisms.

This study aims at investigating how energy strategies of China impact its energy shipping import through a strategic maritime link, the Straits of Malacca and Singapore (SOMS).

Vector error-correction modelling (VECM) is applied to examine the key energy strategies of China influencing crude oil and liquefied natural gas (LNG) shipping import via the SOMS. Strategies investigated include oil storage expansions, government-setting targets to motivate domestic gas production, pipeline projects to diversify natural gas import routes and commercial strategies to ensure oil and gas accessibility and cost-effectiveness.

For the crude oil sector, building up oil storage and diversifying oil import means, routes and sources were found effective to mitigate impacts of consumption surges and price shocks. For the LNG sector, domestic production expansion effectively reduces LNG import. However, pipeline gas import growth is inefficient to relieve LNG shipping import dependency. Furthermore, energy companies have limited flexibility to adjust LNG shipping import volumes via the SOMS even under increased import prices and transport costs.

As the natural gas demand of China continues expanding, utilisation rates of existing pipeline networks need to be enhanced. Besides, domestic production expansion and diversification of LNG import sources and means are crucial.

This study is among the first in the literature using a quantitative approach to investigate how energy strategies implemented in a nation impact its energy shipping volumes via the SOMS, which is one of the most important maritime links that support 40% of the global trades.

The aim of this paper is to study the tribological behaviour of Fe‐C‐Al cast iron at different temperatures using universal pin‐on‐disk machine.

The cold set resin bonded sand mould casting process was employed to develop Fe‐C‐Al cast iron and Fe‐C‐Si cast iron. The microstructures of materials were studied using field emission scanning electron microscope. The wear and friction tests were conducted using universal pin‐on‐disk machine at 25°C, 100°C, 200°C and 300°C temperature. The worn surface was characterized using scanning electron microscopy.

The lower wear rate was found for Fe‐C‐Al cast iron compared to Fe‐C‐Si cast iron and delamination type wear morphology was observed in both types of cast iron materials. The results also showed that the friction coefficient value of Fe‐C‐Al cast iron was lower than that of Fe‐C‐Si cast iron at different temperatures. It can be concluded that the overall tribological behaviour of Fe‐C‐Al cast iron at higher temperatures was better than conventional Fe‐C‐Si cast iron.

The information on the development and tribological properties of the Fe‐C‐Al cast iron at different temperatures is scarce in the literature. The special type of cold set resin bonded sand mould was used for casting this Fe‐C‐Al cast iron material. Therefore, the current study is quite new and it is hoped that it will provide a high value to the automotive and other engineering researchers for the application of this material.

The purpose of this paper is to investigate the dynamic relationship among Gold, Crude oil, Indian Rupee-US Dollar and Stock market-Sensex (gold, oil, dollar and stock market (GODS)) in the pre-crisis, the crisis and the post-crisis periods in the Indian context.

The authors use Johansen’s cointegration technique, Vector Error Correction Model (VECM), Vector Auto Regression, VEC Granger Causality/Block Exogeneity Wald Test, and Granger Causality and Toda Yamamoto modified Granger causality to study long-run relationship and causality.

Johansen’s cointegration test results indicate that there is a long-run equilibrium relationship among the variables in the pre-crisis and the crisis periods but not in post-crisis period. VECM results report that none of four models of the variables show long-run causality in the pre-crisis period. During the crisis period, both crude oil and Sensex models show long-run causality. However, in some cases, results indicate short-run causality. The authors find one-way causality from USD and Sensex to crude oil, and from gold and Sensex to USD. Thus, the authors conclude that the relationship among GODS is dynamic across global financial crisis.

The research findings of this study are vital to the large group of stakeholders and participants of gold, crude oil, US dollar and stock market in emerging economies like India. The results are useful to importers, exporters, government, policy makers, corporate houses, retail investors, portfolio managers, commodity traders, treasury and fund managers, other commercial traders, etc.

This study is one of its kinds as it investigates the relationship among GODS in India in different sub-periods like before, during and after the global financial crisis of 2008. None of the studies compare phase-wise relationship among GODS in the Indian context. The study contributes to the economic theory and the body of knowledge. It highlights the need to revisit the economic theory to explain the interplay mechanism among GODS.